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Proceedings of ICML 2021 Workshop on Theoretic Foundation, Criticism, and Application Trend of Explainable AI


Jul 26, 2021
Quanshi Zhang, Tian Han, Lixin Fan, Zhanxing Zhu, Hang Su, Ying Nian Wu, Jie Ren, Hao Zhang


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Sawtooth Factorial Topic Embeddings Guided Gamma Belief Network


Jun 30, 2021
Zhibin Duan, Dongsheng Wang, Bo Chen, Chaojie Wang, Wenchao Chen, Yewen Li, Jie Ren, Mingyuan Zhou


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A Game-Theoretic Taxonomy of Visual Concepts in DNNs


Jun 21, 2021
Xu Cheng, Chuntung Chu, Yi Zheng, Jie Ren, Quanshi Zhang

* 12 pages 

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A Simple Fix to Mahalanobis Distance for Improving Near-OOD Detection


Jun 16, 2021
Jie Ren, Stanislav Fort, Jeremiah Liu, Abhijit Guha Roy, Shreyas Padhy, Balaji Lakshminarayanan


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Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep Learning


Jun 07, 2021
Zachary Nado, Neil Band, Mark Collier, Josip Djolonga, Michael W. Dusenberry, Sebastian Farquhar, Angelos Filos, Marton Havasi, Rodolphe Jenatton, Ghassen Jerfel, Jeremiah Liu, Zelda Mariet, Jeremy Nixon, Shreyas Padhy, Jie Ren, Tim G. J. Rudner, Yeming Wen, Florian Wenzel, Kevin Murphy, D. Sculley, Balaji Lakshminarayanan, Jasper Snoek, Yarin Gal, Dustin Tran


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Exploring the Limits of Out-of-Distribution Detection


Jun 06, 2021
Stanislav Fort, Jie Ren, Balaji Lakshminarayanan

* S.F. and J.R. contributed equally 

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Learning Baseline Values for Shapley Values


May 22, 2021
Jie Ren, Zhanpeng Zhou, Qirui Chen, Quanshi Zhang


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Probabilistic Mixture-of-Experts for Efficient Deep Reinforcement Learning


Apr 19, 2021
Jie Ren, Yewen Li, Zihan Ding, Wei Pan, Hao Dong


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Learning to Remove: Towards Isotropic Pre-trained BERT Embedding


Apr 12, 2021
Yuxin Liang, Rui Cao, Jie Zheng, Jie Ren, Ling Gao


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Uniting Heterogeneity, Inductiveness, and Efficiency for Graph Representation Learning


Apr 11, 2021
Tong Chen, Hongzhi Yin, Jie Ren, Zi Huang, Xiangliang Zhang, Hao Wang

* Manuscript is under review 

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Does Your Dermatology Classifier Know What It Doesn't Know? Detecting the Long-Tail of Unseen Conditions


Apr 08, 2021
Abhijit Guha Roy, Jie Ren, Shekoofeh Azizi, Aaron Loh, Vivek Natarajan, Basil Mustafa, Nick Pawlowski, Jan Freyberg, Yuan Liu, Zach Beaver, Nam Vo, Peggy Bui, Samantha Winter, Patricia MacWilliams, Greg S. Corrado, Umesh Telang, Yun Liu, Taylan Cemgil, Alan Karthikesalingam, Balaji Lakshminarayanan, Jim Winkens

* Under Review, 19 Pages 

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Game-theoretic Understanding of Adversarially Learned Features


Mar 12, 2021
Jie Ren, Die Zhang, Yisen Wang, Lu Chen, Zhanpeng Zhou, Xu Cheng, Xin Wang, Yiting Chen, Jie Shi, Quanshi Zhang


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ZeRO-Offload: Democratizing Billion-Scale Model Training


Jan 18, 2021
Jie Ren, Samyam Rajbhandari, Reza Yazdani Aminabadi, Olatunji Ruwase, Shuangyan Yang, Minjia Zhang, Dong Li, Yuxiong He


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A Unified Approach to Interpreting and Boosting Adversarial Transferability


Oct 08, 2020
Xin Wang, Jie Ren, Shuyun Lin, Xiangming Zhu, Yisen Wang, Quanshi Zhang


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Revisiting One-vs-All Classifiers for Predictive Uncertainty and Out-of-Distribution Detection in Neural Networks


Jul 10, 2020
Shreyas Padhy, Zachary Nado, Jie Ren, Jeremiah Liu, Jasper Snoek, Balaji Lakshminarayanan


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Interpreting and Disentangling Feature Components of Various Complexity from DNNs


Jun 29, 2020
Jie Ren, Mingjie Li, Zexu Liu, Quanshi Zhang


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SummAE: Zero-Shot Abstractive Text Summarization using Length-Agnostic Auto-Encoders


Oct 02, 2019
Peter J. Liu, Yu-An Chung, Jie Ren

* first two authors contributed equally 

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Likelihood Ratios for Out-of-Distribution Detection


Jun 07, 2019
Jie Ren, Peter J. Liu, Emily Fertig, Jasper Snoek, Ryan Poplin, Mark A. DePristo, Joshua V. Dillon, Balaji Lakshminarayanan


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Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift


Jun 06, 2019
Yaniv Ovadia, Emily Fertig, Jie Ren, Zachary Nado, D Sculley, Sebastian Nowozin, Joshua V. Dillon, Balaji Lakshminarayanan, Jasper Snoek


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Explaining Neural Networks Semantically and Quantitatively


Dec 18, 2018
Runjin Chen, Hao Chen, Ge Huang, Jie Ren, Quanshi Zhang


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To Compress, or Not to Compress: Characterizing Deep Learning Model Compression for Embedded Inference


Oct 21, 2018
Qing Qin, Jie Ren, Jialong Yu, Ling Gao, Hai Wang, Jie Zheng, Yansong Feng, Jianbin Fang, Zheng Wang

* 8 pages, To appear in ISPA 2018 

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Active Learning for Wireless IoT Intrusion Detection


Aug 04, 2018
Kai Yang, Jie Ren, Yanqiao Zhu, Weiyi Zhang

* 7 pages, 4 figures, accepted by IEEE Wireless Communications 

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An End-to-End Compression Framework Based on Convolutional Neural Networks


Aug 02, 2017
Feng Jiang, Wen Tao, Shaohui Liu, Jie Ren, Xun Guo, Debin Zhao

* Submitted to IEEE Transactions on Circuits and Systems for Video Technology 

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